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Automatic arima modelling by the cartesian search algorithm

✍ Scribed by Rune Höglund; Ralf Östermark

Book ID
102842488
Publisher
John Wiley and Sons
Year
1991
Tongue
English
Weight
647 KB
Volume
10
Category
Article
ISSN
0277-6693

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✦ Synopsis

Abstract

In the present study we report on the development and test results of a Cartesian ARIMA Search Algorithm, designed for automatic generation of univariate models for time series data within specified parameter intervals of the identification and estimation stages. Model retention is determined within a preselected set of statistics. By interpreting these statistics as dimensions of the constructed criterion space, we obtain a subset of non‐dominated models according to the rule of maximum dispersion over the efficient set. The CARIMA algorithm allows free specification of the number of criteria used in the runs. The algorithm was tested with both simulated and real economic data. The results based on simulated data indicate that the precision of the CARIMA algorithm is lower for seasonal models and higher for non‐seasonal ones, thus suggesting an inverse relationship between algorithm performance and model complexity.

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